AI and Machine Learning-Driven Innovations in Macroeconomics

Abstract

With the rapid development of Artificial Intelligence (AI) and Machine Learning (ML) technologies, the research methods and practices in macroeconomics are undergoing profound transformations. Traditional economic analysis methods often rely on historical data and empirical models, facing challenges such as data lag, information asymmetry, and insufficient predictive accuracy. The introduction of AI and ML has provided new approaches and tools for economic research, demonstrating wide application prospects, particularly in the construction of novel economic indicators, economic forecasting, policy analysis, and financial market analysis. This paper reviews the current status and future trends of AI and ML applications in macroeconomics, with a focus on the use of alternative data in constructing economic indicators, the integration of machine learning with traditional economic forecasting models, the potential and challenges of large language models in economic policy analysis, and the application of machine learning in financial market analysis.